Mismatch between warning information and protective behavior: Why experts + AI < 2?

Warning information plays a vital role in encouraging disaster preparedness among residents. Using survey experiment data from 619 respondents in China, this study examines how warning messages from AI, experts, and a combination of the two influence public disaster preparedness behaviors and whether the degree of impact differs between these sources. The findings reveal that warnings from AI, experts, and a combination of those two sources significantly affect disaster preparedness behaviors. Notably, and contrary to conventional expectations, the combined warnings from AI and experts do not result in a mutually strengthening effect. Instead, a crowding-out effect is observed, whereby the combined impact is less than the sum of individual effects ("Experts + AI < 2"). This outcome can be attributed to information fatigue, suggesting that information overload does not always benefit the public but instead often becomes a burden. Additionally, the influence of AI-driven warnings on preparedness varies substantially with respondents' educational levels. The insights provided by this study hold practical implications for government agencies in promoting public disaster preparedness.

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Publication Details

Journal
Risk Analysis
Published
2025-05-04
DOI
https://doi.org/10.1111/risa.70030
Citations
1
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
4.20

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article

Mismatch between warning information and protective behavior: Why experts + AI < 2?

Qi Bian, Ben Ma, Lili Wang, L. Xin
1 citations
Risk Analysis
Disaster Management and Resilience
4.20
article

Mismatch between warning information and protective behavior: Why experts + AI < 2?

Qi Bian, Ben Ma, Lili Wang, L. Xin
article en
1 citations

Abstract

Warning information plays a vital role in encouraging disaster preparedness among residents. Using survey experiment data from 619 respondents in China, this study examines how warning messages from AI, experts, and a combination of the two influence public disaster preparedness behaviors and whether the degree of impact differs between these sources. The findings reveal that warnings from AI, experts, and a combination of those two sources significantly affect disaster preparedness behaviors. Notably, and contrary to conventional expectations, the combined warnings from AI and experts do not result in a mutually strengthening effect. Instead, a crowding-out effect is observed, whereby the combined impact is less than the sum of individual effects ("Experts + AI < 2"). This outcome can be attributed to information fatigue, suggesting that information overload does not always benefit the public but instead often becomes a burden. Additionally, the influence of AI-driven warnings on preparedness varies substantially with respondents' educational levels. The insights provided by this study hold practical implications for government agencies in promoting public disaster preparedness.

Risk AnalysisVol. 45(12)
Qingdao University (CN), Shandong University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Shandong Province, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 8%
Disaster Management and Resilience
4.20
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Mismatch between warning information and protective behavior: Why experts + AI &lt; 2? — Qi Bian, Ben Ma, et al. · Risk Analysis (2025) | TGRS Research Map | TGRS